A5074976831- Advanced Multi-Objective Optimization Algorithms
- Metaheuristic Optimization Algorithms Research
- Optimization and Packing Problems
- Advanced Manufacturing and Logistics Optimization
- Vehicle Routing Optimization Methods
- 3D IC and TSV technologies
- Real-Time Systems Scheduling
- Scheduling and Timetabling Solutions
- Wireless Networks and Protocols
- Advanced Clustering Algorithms Research
- IPv6, Mobility, Handover, Networks, Security
- Simulation and Modeling Applications
- Real-time simulation and control systems
- Business Strategy and Innovation
- Facility Location and Emergency Management
- Simulation Techniques and Applications
- VLSI and FPGA Design Techniques
- Face and Expression Recognition
- Complexity and Algorithms in Graphs
- Reservoir Engineering and Simulation Methods
- Hydrological Forecasting Using AI
- Software Reliability and Analysis Research
- Electronic Packaging and Soldering Technologies
- Radiomics and Machine Learning in Medical Imaging
- Engineering and Test Systems
Northeastern University
2018-2024
Xi'an University of Architecture and Technology
2023
Huazhong University of Science and Technology
2017-2022
Daqing Oilfield of CNPC
2022
Daqing Oilfield General Hospital
2022
Central China Normal University
2021
Université d'Angers
2020-2021
Guangdong Polytechnic Normal University
2021
Tongji Hospital
2020
Zhongyuan University of Technology
2017
In the distributed integrated modular avionics (DIMA), it is desirable to assign DIMA devices installation locations of aircraft for obtaining optimal quality and cost, subject resource safety constraints. Currently, routine device assignments in are conducted manually or by experience, which becomes more difficult with increasing number devices. Especially, face large-scale assignment problems (DAPs), manual allocation will become an almost impossible task. this paper, a bi-objective...
Flood forecasting plays an important role in flood control and water resources management. Recently, the data-driven models with a simpler model structure lower data requirement attract much more attentions. An extreme learning machine (ELM) method, as typical advantages of faster process stronger generalization ability, has been taken effective tool for forecasting. However, ELM may suffer from local minima some cases because its random generation input weights hidden layer biases, which...
Portfolio optimization problems involve selection of different assets to invest in order maximize the overall return and minimize risk simultaneously. The complexity optimal asset allocation problem increases with an increase number available select from for investing. becomes computationally challenging when there are more than a few hundreds from. To reduce large‐scale portfolio optimization, two preselection procedures that consider individual pairwise correlation remove may not...
Abstract In the present study, three alcohol precipitation polysaccharides fractions (IOP40, IOP60, and IOP80) are isolated from Inonotus obliquus (IOP). vitro starch digestion experiments suggest that IOP40 IOP60 show stronger inhibitory effects than crude polysaccharides. Inhibition kinetics demonstrates has reversible anti‐competitive effect on α‐glucosidase. I. also have a significantly of dough. Furthermore, in vivo studies prove can inhibit increase postprandial blood glucose level. is...
Mobility in a wireless heterogeneous scenario which the mobile devices are able to connect more than one access technology requires new architectural development for network connectivity management. The present paper describes and evaluates set of options integrating novel discovery selection functionality 3GPP evolved packet core enables an operator manage connections devices. As design here presented consider different levels control on mobility at cost interfaces procedures, evaluation...
Currently, real-world complex engineering problems often have more than three objectives that need to be optimized simultaneously. Existing algorithms for solving them mostly rely on the shape of Pareto front maintain diversity, which makes it difficult effectively balance convergence and diversity solutions. To address above problems, a many-objective evolutionary algorithm based indicator selection adaptive angle estimation (MaOEA-ISAE) is proposed in this paper. Firstly, unit vector...
Abstract The knapsack problem (KP) with forfeits is a generalized KP that aims to select some items, among set of candidate maximize profit function without exceeding the capacity. Moreover, forfeit cost incurred and deducted from when both incompatible items are placed in knapsack. This relevant model for number applications however computationally challenging. We present hybrid heuristic method tackling this combines evolutionary search adaptive feasible infeasible find high‐quality...
In this study, radiomic based predictive models using MRI can non-invasively assess Tert genotype of Oligodendrogliomas(ODs). Compared With histopathological assessment,radiomic has its unique advantages in assessing ODs. such as noninvasive, more comprehensive information about tumor heterogeneity and repeatable. Furthermore,radiomic clearly directly show Therefore, it is a potential alternative to invasive biopsy.
Mobility in a wireless heterogeneous scenario which the mobile devices are able to connect more than one access technology available their vicinity requires re-consideration on network reselection mechanisms. The present paper describes and evaluates opportunity of introducing novel procedures enable provider optimize allocation users different networks using as central concept that handovers can should be triggered by modifications resources required order overall usage environment. This is...